Common method variance or measurement bias? The problem and possible solutions
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- "Different sources of method effects are suggested, including the form or the length of the response scales and the form or complexity of the questions. We agree that CMV and CMB can be found in survey data, especially in the case of self-report surveys, because we understand that the respondent as a rater is a source of method variance; that is, variance not intended by the researcher (Spector & Brannick, 2009). However, we do not believe that this CMV stems from the method itself given that the latter is a constant. "
ABSTRACT: Since the idea of method variance was inspired by D. T. Campbell and Fiske in 1959, many papers have demonstrated an ongoing debate about both its nature and impact. Often, method variance entails an upward bias in correlations among observed variables—common method bias. This article reports a split-ballot multitrait–multimethod experimental design for estimating 2 opposite biases: the upward biasing method variance from the reaction to the length of the response scale and the position of the survey items in the questionnaire and the downward biasing effect of poor data quality. The data are derived from self-reported behavior related to emotional and social competencies. This article illustrates a methodology to estimate common method bias and its components: common method scale variance, common method occasion variance, and the attenuation effect due to measurement errors. The results show that common method variance has a much smaller impact than random and systematic measurement errors. The results also corroborate previous findings: the greater reliability of longer scales and the lower reliability of items placed toward the end of the survey.Structural Equation Modeling A Multidisciplinary Journal 08/2014; 21(4):506-607. · 4.18 Impact Factor
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- "We do not resolve this dispute in our research, because other papers handle this discussion very well. See, for example, Spector and Brannick (2009) or Podsakoff et al. (2003). Overall, our research is well aligned with the perspective that a method is a mechanism where by an item triggers unrelated personality traits within the respondent. "
ABSTRACT: This research analyzes the effects of common method variance (CMV) on parameter estimates in bivariate linear, multivariate linear, quadratic, and interaction regression models. The authors demonstrate that CMV can either inflate or deflate bivariate linear relationships, depending on the degree of symmetry with which CMV affects the observed measures. With respect to multivariate linear relationships, they show that common method bias generally decreases when additional independent variables suffering from CMV are included in a regression equation. Finally, they demonstrate that quadratic and interaction effects cannot be artifacts of CMV. On the contrary, both quadratic and interaction terms can be severely deflated through CMV, making them more difficult to detect through statistical means.Organizational Research Methods 07/2010; 13(3):456-476. DOI:10.1177/1094428109351241 · 3.26 Impact Factor
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